skysight-inc/HackerNews huggingface dataset:
>> It's 2 days after Christmas, too early to know the impact of the purchases made based on what AI recommended, either positive or negative.

No worries, I can tell you what to expect: nothing. No effect. Zilch. Nada. Zero. Those beauty creams are just a total scam and that's obvious from the fact they're targetted just as well to women who don't need them (young, good skin) as to ones who do (older, bad skin).

About the only thing the beauty industry has figured out really works in the last five or six decades is Tretinoin, but you can use that on its own. Yet it's sold as one component in creams with a dozen others, that do nothing. Except make you spend money.
In a democracy, you would do something like tax this real estate, heavily, for the benefit of the people living in this locale. Hand it back out to these locals ("biological human voters") as free services, goods, or cash as you prefer.

In inhabited buildings, that gets passed on to the residents. In uninhabited buildings, it comes straight out of the investors ("land-hoarders").
They are applying a "it worked for me, therefore it works for all" mentality.

And then you do the same thing in the next line...
LLMs are fuzzy compression with a really good natural language parser...
My impression was that the variance is high enough that i have to learn / swap new vocabulary with every new person in my social circles. I don't see the convergence you are talking of.
Believe me, if they could use another LLM to audit an LLM, they would have done that already.

It's inherit to transformers that they predict the next most likely token, its not possible to change that behavior without making them useless at generalizing tasks (overfitting).

LLMs run on statistics, not logic. There is no fact checking, period. There is just the next most likely token based on the context provided.
The point of research is not if it's or isn't useful for practical purposes.
> If the tokens are bit-for-bit-identical, where does the non-determinism come in?

By design, most LLM’s have a randomization factor to their model. Some use the concept of “temperature” which makes them randomly choose the 2nd or 3rd highest ranked next token, the higher the temperature the more often/lower they pick a non-best next token. OpenAI described this in their papers around the GPT-2 timeframe IIRC.
I certainly did not mean to imply that every browser fingerprinting vulnerability is due to Google née Doubleclick. What did I say to make you think so?

And from a technical perspective, Accept-language doesn't seem terribly hard to mitigate - exactly one language at a time, and UI that allows a user to easily change to another, as if it's part of the logical URL. It's all the javascript APIs, especially the graphics ones with their loads of weakly-defined behavior, that are especially pernicious.
At present, LLMs work well with smaller chunks of code at time.

Check out these tips for using Aider (a CLI based LLM code assisntant)
https://aider.chat/docs/usage/tips.html

It can ingest the entire codebase (up to its context length), but for some reason, I’ve always had much higher quality chats with smaller bite-sized pieces of code.
The new science is… podcasts. I fell asleep listening to Ologies and dreamed I was building a new cabin in the woods. (She had a cabin architect on as the guest.)
Base Blocks Air: Air Powered Full Body at Home Resistance Training
>I kind of thought that was the point of the current structure.

Yes, it is but if we only stopped the analysis right there, we could take pleasure in the fact that Sam Altman checkmated himself in his own blog post. "Dude, the non-profit is _supposed_ to control the profit company because that's how you formed the companies in the first place! Duh!!!"

To go beyond that analysis, we have to at least entertain (not "agree" but just _entertain_ for analysis) ... what Sam is saying:

- the original non-profit and profit structure was a mistake that was based on what they thought they knew at the time. (They thought they could be a "research" firm.)

- having a non-profit control the profit becomes a moot point if the for-profit company becomes irrelevant in the marketplace.

Here is a key paragraph:

>The hundreds of billions of dollars that major companies are now investing into AI development show what it will really take for OpenAI to continue pursuing the mission. We once again need to raise more capital than we’d imagined. Investors want to back us but, at this scale of capital, need conventional equity and less structural bespokeness.

In other words, let's suppose the old Friendster social network was structured as "non-profit-board-controlling-a-for-profit-Friendster" like OpenAI. The ideals of the "non-profit being in control" is a moot point when a competitor like Facebook makes non-profit-Friendster irrelevant.

Or put another way, pick any hard problem today (self-driving, energy discovery, etc) that requires billions of investment and hypothetically create a new company to compete in that space. Would creating that company as a non-profit-controlling-the-profit-company confer any market advantage or would it be a handicap? It looks like it's a handicap.

OpenAI is finding it hard to compete for investors' billions in the face of Tesla's billions spent on 50000 GPU supercluster, Google billions spent on Gemini, Anthropic billions spent on Claude, Alibaba's billions, etc. OpenAI doesn't have an unassailable lead with ChatGPT.

The issue is Sam Altman & OpenAI look bad because he and the investors want to use the existing "OpenAI" brand name in a restructured simpler for-profit company. But to outsiders, it looks like a scam or bait-and-switch. Maybe they could have done an alternative creative procedure such as spin up a totally new for-profit company called ClosedAI to take OpenAI's employees and then pay a perpetual ip license to OpenAI. That way, CloseAI is free of encumbrances from OpenAI's messy structure. But then again, Elon Musk would still probably file another lawsuit calling those license transfers as "bad faith business dealings".
Ask HN: What's the best site to track H5N1 progression?
Is there a good wastewater tracker? I see that the CDC is tracking but they seem to be giving only yes/no, rather than quantitative.
I don’t see how it would because at the end of the day a model is like a program… input->output. This seems infinitely useful and we are just starting to understand how to use this new way of computing.
Nice - these two were my go-tos as well. The nose-plug one felt especially weird once you realized what was happening.
The trained model is just a bunch of statistics. To use those statistics to generate text you need to "sample" from the model. If you always sampled by taking the model's #1 token prediction that would be deterministic, but more commonly a random top-K or top-p token selection is made, which is where the randomness comes in.
Hopping in to say that I’ve used mochi very regularly for over a year and love it. It’s definitely an aesthetic improvement over Anki. I’m kind of confused why it isn’t more popular - I remember doing a bunch of research on SR software and not finding any I liked, and then only finding Mochi by chance when the creator left an HN comment
Aider with claude sonnet is probably all I needed to get my programming cycle up to speed. I don't think I want anything more as a developer.

That said, it still makes mistakes
To work steal, you must have work to steal. If you always have work to steal, you have a CPU problem, not a CPU fabric problem. CPU fabrics are good for when you have some sort of task that is sort of parallel, but also somehow requires a lot of cross-talk between the tasks, preferably of a very regular and predictable nature, e.g., not randomly blasting messages of very irregular sizes like one might see in a web-based system, but a very regular "I'm going to need exactly 16KB per frame from each of my surrounding 4 CPUs every 25ms". You would think of using a GPU on a modern computer because you can use all the little CPUs in a GPU, but the GPU won't do well because those GPU CPUs can't communicate like that. GPUs obtain their power by forbidding communication within cells except through very stereotyped patterns.

If you have all that, and you have it all the time, you can win on these fabrics.

The problem is, this doesn't describe very many problems. There's a lot of problems that may sort of look like this, but have steps where the problem has to be unpacked and dispatched, or the information has to be rejoined, or just in general there's other parts of the process that are limited to a single CPU somehow, and then Amdahl's Law murders your performance advantage over conventional CPUs. If you can't keep these things firing on all cylinders basically all the time, you very quickly end up back in a regime where conventional CPUs are more appropriate. It's really hard to feed a hundred threads of anything in a rigidly consistent way, whereas "tasks more or less randomly pile up and we dispatch our CPUs to those tasks with a scheduler" is fairly easy, and very useful.
Every Mantra Has a Counter Mantra
I agree that spaced repetition is essential and Anki is just the main player. I think the ideal product would combine: a flashcard app like anki, automated emails you can reply to, audio nudges and more ...
Please don’t mistake explanation for excuse.
Ask your ai search engine of choice what the Dunning–Kruger effect is
Not outsourcing at all - you're are an engineer using the tools that make sense to solve a problem. The core issue with identifying as just a coder is that code is just one of many potential tools to solve a problem.
I agree with this irony.

That said, combining multiple ais and multiple programs together may mitigate this.
Yes, the Eames were much more than furniture designers (often for Herman Miller) - they also made films like the famous "Powers of Ten"

https://www.youtube.com/watch?v=0fKBhvDjuy0
No, just enforce the DMCA. Youtube has setup this fake DMCA system where they are acting like they enforcing DMCA but not actually.

DMCA has protection for creators. You can say "Copyright holder is wrong, put my content back up and I'll see them in court." and "They did this maliciously, I'll see them in court."

However, YouTube fake DMCA system is using the provision of "We don't have to host any content we don't want to." so creators are stuck dealing with corporate bureaucracy. Personally, I think YouTube should lose DMCA protection if they want to run this side system.
Said like a true teacher.
When the consequence is paying a fine/settlement, it means the law is only for poor people.
Anyone downvoting, please be aware that you are downvoting the AI's answer!

:)
I haven’t had many lucid dreams, but this mirrors my experience. Whenever I realise I’m in a lucid dream, the trick to keep me in it is to manage how much control I exert. If I start to direct it too much I can feel myself waking up and have to “let go” and not react to what’s happening, letting the dream carry me wherever it seems fit. After a while I begin to feel consciousness drifting away and can again exert some modicum of control to explore my surroundings. Rinse and repeat, until I inevitably wake up.
Maybe I'm just a malcontent, but for me this begs the question: couldn't this be used in reverse as activism?

Like, if enough people used enough fake accounts and started relentlessly submitting takedown requests on the biggest channels making the most revenue, not only would YouTube start to see the revenue issue, but the big channels would start making noise. Go after one troll sending the requests, another one takes its place. Seems like it would force YouTube to at least reconcile with this particular flaw in the system.
I imagine you're asking about coding help. For that, I think you should qualify any answer you get with the user's most commonly used language (and framework, if applicable).

In my experience, Claude Sonnet 3.5 (3.6?) has been unbeatable. I use it for Rust. Making sense of compiler errors, rubberducking, finding more efficient ways to write some function and, truth be told, some times just plain old debugging. More than once, I've been able to dump a massive module onto the chat context and say "look, I'm experiencing this weird behavior but it's really hard to pin down what's causing it in this code" and it pointed to the exact issue in a second. That alone is worth the price of admission.

Way better than ChatGPT 4o and o-1, in my experience, despite me saying the exact opposite a few months ago.
what is an introvert then? because these arguments also apply on introverts
This. To add some words why this is important:

Given the remote-first container-based world we're heading towards, decoupling UI (terminal emulator) from its "backend" (tmux, code-server) is a great design decision, which I think will ultimately define what the "next generation" of terminal emulators is. Imagine being able to open tabs directly on remote host, reconnect without losing state, etc, all while using native UI (so Cmd+T to open new tab, Cmd+F to search, etc). Productivity game changer, which currently only the iTerm2 users can fully enjoy.

Ptyxis (putting its backend in running containers), WezTerm (native handling of ssh sessions) and VSCode's terminal (starting a proprietary code-server binary and connecting to its TCP port) have reached some of this functionality, but in their design they need some out-of-band mechanisms to handle the connections, ultimately limiting the scenarios they can handle.

Meanwhile tmux -CC [0] and ht [1] are sending both their control channel and data channel over the opened terminal itself (in-band), making them flexible enough to support any configuration. Something complex like `ssh jumpbox -- ssh prod -- podman exec -it prod /bin/bash -- tmux -CC` should just work, as if everything was running on your local machine.

[0] https://github.com/tmux/tmux/wiki/Control-Mode

[1] https://github.com/andyk/ht
Nah, the trick with o3 solving IQ tests seems to be that they bruteforce solutions and then pick the best option. That's why calls that are trivial for humans end up costing a lot.

It still can't think and it won't think.

LANGUAGE models (keyword: language) is a language model, it should be paired with a reasoning engine to translate the inner thought of the machine into human language. It should not be the source of decisions because it sucks at doing so, even though the network can exhibit some intelligence.

We will never have AGI with just a language model. That said, most jobs people do are still at risk, even with chatgpt-3.5 (especially outside of knowledge work, where difficult decisions need to be taken). So we'll see the problems with AGI and the job market way earlier than AGI, as soon as we apply robotics and vision models + chatgpt 3.5 level intelligence. Goodbye baristas, goodbye people working in factories.

Let's start working on a reasoning engine so we can replace those pesky knowledge workers too.
We vote. And we did.
This also occurred at least once with Canada/US military (but still Korean aircraft) during the panic on September 11, 2001 — an aircraft that was actually just doing normal stuff, very nearly got shot down.

https://en.wikipedia.org/wiki/Korean_Air_Flight_085
I want to do that if I ever find the time. Adding a date to the database entries, and some code to throw an old word in here and there based on spaced repetition best practices.
you can, only if you have the critical amount of self confidence, appetite for conflict, lack the fear of losing them, and/or have another group of people who you can substitute after their loss. Thats a big ask for all but the most socially endowed of us.
If you qualify country A's actions as "starting a war" then country B had started many dozens of wars themselves in the previous decade, and subsequent one.
Well if it applied, someone should train a model that tells LLM and human content apart for automated rejection.
I was really sad when people sued the NSA over developing Accumulo[0].

[0]: https://www.techdirt.com/2012/07/18/senate-not-concerned-abo...
Why do you think a video capture of a computer program would infringe the copyrights of the program's creators?
> go and investigate what is currently considered state of the art for trading algorithms.

These are not LLMs but algorithms written and designed by human minds. It is unfortunate that AI has become a catch-all word for any kind of machine learning.
I’m convinced New Years Resolutions are at least partly successful, if for nothing else that the 6-8 weeks of holiday distractions (family, travel, gift shopping, holiday treats, etc) are finally over. January is a blank canvas where you can finally find some traction.
Someone didn't read the link.
Looks interesting. I'm playing around with it on Linux (with Xfce), but can't figure out how to get rid of the CSD header bar / hamburger menu and use a normal menu bar instead. I see Mac screenshots with a normal Mac-style menu bar, but I don't see how to enable the equivalent on Linux. The `window-theme` and `window-decoration` options do not seem to do anything.
If you read between the lines in the article, YouTube literally just said 94% of takedowns are real.
I said "fast and native" because none of browsers made it impossible to inspect the flamegraph.

> In this case it is though, so I don't see why it would be a problem for it to be web based.

Would you like to say that your browser is able to render the flamegraph https://laladrik.xyz/img/pic.svg and inspect it? As I wrote in the article (the first paragraph), it takes a couple of seconds to render the graph, and nothing happens when I press on a frame. Could you check it, please? If your browser renders it as fast enough and allows to open a frame, please, let me know how could I improve any of browsers. I would really appreciate it.
This isn't about if LLMs are useful, it's about how useful can they become. We are trying to understand if there is a path forward to transformative tech, or are we just limited to a very useful tool.

It's a valid conversation after ~3 years of anticipating the world to be disrupted by this tech. So far it has not delivered.

Wikipedia did not change the world either, it's just a great tool that I use all the time

As for software, it performs ok. I give up on it most of the time if I am trying to write a whole application. You have to acquire a new skill, prompt engineering, and feverish iteration. It's a frustrating game of whack-a-mole and I find it quicker to write the code myself and just have the LLM help me with architecture ideas, bug bashing, and it's also quite good at writing tests.

I'd rather know the code intimately so I can more quickly debug it than have an LLM write it and just trust it did it well.
They wouldn't even need to go that far. The current way YouTube's system works is so deck-stacked against the creator to a ludicrous degree. Basically any "copyright holder" just has to say "this belongs to me" and YouTube immediately funnels all revenue for the video to that holder, with basically no oversight whatsoever, and as anyone in the space will tell you, a video makes 90% of it's money in the first few days which means these holders can grab the monetization right out from under a creator and steal just, all their fucking money. It's ridiculous.

Like all you would have to do to, perhaps not fix, but heavily mitigate this, would be to have YouTube just... hold onto the revenue until the dispute is resolved. It's barely even a change. And most of the time, when creators do counter the claims, they're eventually dropped but again because of how that system works, YouTube has already funneled all their money to the claimant, irrespective of the determined validity of the claim. And it would discourage bullshit claims because even as low-rent a scam as this is, it is some amount of work, and if there's no payout, you necessarily reduce the number of scammers who will attempt it.

I don't know if that's a DMCA thing, I admittedly haven't researched it in a long time, but I don't see how that would put YouTube at any kind of liability. Any reader, do feel free to correct me.
https://en.wikipedia.org/wiki/Quantum_teleportation

> (...) quantum teleportation only transfers quantum information. The sender does not have to know the particular quantum state being transferred nor the location of the recipient, but to complete the quantum teleportation, classical information needs to be sent from sender to receiver. Because classical information needs to be sent, quantum teleportation cannot occur faster than the speed of light.

From here it's mind blowing until the part where classical information needs to be sent. Then it only seems useful as a way to transfer quantum state safely and undetected. It's really cool that the classical information can be broadcasted, so you can keep the recipient's location secret.
Maybe quantum cryptographic keys, if that's a thing, can be sent this way, or a channel that just teleports quantum data without a chance of of being overheard can be setup.
If you want all the dollars fine, but pretending you're doing us a favor is creepy.
Bench accounting services shutting down
first winds of winter coming...
How would the a 12 year old with ChatGPT recognize complicateed errors?
You still need experience to check the code not only the result otherwise you get this

https://news.ycombinator.com/item?id=42235630
> might

I found their post helpful, and not an attempt to diagnose.
chatgpt how to fix bash: spaceman: command not found
Reading the o1 announcement you could have been saying the same thing a year ago yet it's worse than Claude in practice and if it was all that's available - I wouldn't even use it if it was free - it's that bad.

If OpenAI has demonstrated one thing is that they are a hype production machine and they are probably getting ready for next round of investment. I wouldn't be surprised if this model was equally useless as o1 when you factor in performance and price.

At this point they are completely untrustworthy and untill something lands publicly for me to test it's safe to ignore their PR as complete BS.
It feels good to hear support for printf-debugging coming from such esteemed corner. I have been doing that for a significant majority of my career instead of dropping into debugger. The side effect is you become pretty good at crafting meaningful logs.
They literally used footage of one of their Iskander missiles striking a Syrian hospital in a highlight reel for the effectiveness of that missile.

https://www.forbes.com/sites/sebastienroblin/2021/03/01/mosc...
> Coding as a profession is completely obsolete.

Citation needed.
K8GB – A cloud native Kubernetes Global Balancer
A Global Service Load Balancing solution with a focus on having cloud native qualities and work natively in a Kubernetes context.

```
apiVersion: k8gb.absa.oss/v1beta1
kind: Gslb
metadata:
name: test-gslb-failover
namespace: test-gslb
spec:
resourceRef:
apiVersion: networking.k8s.io/v1
kind: Ingress
matchLabels: # ingresses.networking.k8s.io resource selector
app: test-gslb-failover
strategy:
type: failover # Global load balancing strategy
primaryGeoTag: eu-west-1 # Primary cluster geo tag
```
Thanks for the recommendation. Looks like they're on Kindle Unlimited so I'll definitely give them a try
My impression is that (a) extraverts and introverts both have some mutual incomprehension, but that (b) this is greater in extraverts.

Am I just projecting my own introvert bias onto (b) here? Or is there something structural that is responsible for this? Or am i completely wrong about (a)? Thoughts?
I lucid dream myself, which I recognize as impossible to productize. Yet, the productization of lucid dreaming will be attempted, will be successful, and will have nothing to do with lucid dreaming, it will be marketing tie ins with all manner of nonsense.